TY - JOUR
T1 - Maximizing the Geometric Mean of User-Rates to Improve Rate-Fairness
T2 - Proper vs. Improper Gaussian Signaling
AU - Yu, Hongwen
AU - Tuan, Hoang Duong
AU - Dutkiewicz, Eryk
AU - Poor, H. Vincent
AU - Hanzo, Lajos
N1 - Funding Information:
This work was supported in part by the Australian Research Councils Discovery Projects under Grant DP190102501, in part by the Engineering and Physical Sciences Research Council through COALESCE under Project EP/P034284/1 and Project EP/P003990/1, and in part by the European Research Council’s Advanced Fellow Grant QuantCom under Grant 789028.
Publisher Copyright:
© 2002-2012 IEEE.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - This paper considers a reconfigurable intelligent surface (RIS)-aided network, which relies on a multiple antenna array aided base station (BS) and an RIS for serving multiple single antenna downlink users. To provide reliable links to all users over the same bandwidth and same time-slot, the paper proposes the joint design of linear transmit beamformers and the programmable reflecting coefficients of an RIS to maximize the geometric mean (GM) of the users' rates. A new computationally efficient alternating descent algorithm is developed, which is based on closed-forms only for generating improved feasible points of this nonconvex problem. We also consider the joint design of widely linear transmit beamformers and the programmable reflecting coefficients to further improve the GM of the users' rates. Hence another alternating descent algorithm is developed for its solution, which is also based on closed forms only for generating improved feasible points. Numerical examples are provided to demonstrate the efficiency of the proposed approach.
AB - This paper considers a reconfigurable intelligent surface (RIS)-aided network, which relies on a multiple antenna array aided base station (BS) and an RIS for serving multiple single antenna downlink users. To provide reliable links to all users over the same bandwidth and same time-slot, the paper proposes the joint design of linear transmit beamformers and the programmable reflecting coefficients of an RIS to maximize the geometric mean (GM) of the users' rates. A new computationally efficient alternating descent algorithm is developed, which is based on closed-forms only for generating improved feasible points of this nonconvex problem. We also consider the joint design of widely linear transmit beamformers and the programmable reflecting coefficients to further improve the GM of the users' rates. Hence another alternating descent algorithm is developed for its solution, which is also based on closed forms only for generating improved feasible points. Numerical examples are provided to demonstrate the efficiency of the proposed approach.
KW - Reconfigurable intelligent surface
KW - geometric mean maximization
KW - nonconvex optimization algorithms
KW - proper and improper Gaussian signaling
KW - transmit beamforming
KW - trigonometric function optimization
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U2 - 10.1109/TWC.2021.3095174
DO - 10.1109/TWC.2021.3095174
M3 - Article
AN - SCOPUS:85110862589
SN - 1536-1276
VL - 21
SP - 295
EP - 309
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 1
ER -